Philipp Koellinger

The paper examines how polygenic indices for educational attainment change across birth cohorts and regions in Germany, finding stronger associations in recent cohorts and the East but weaker effects for women.

The paper updates a polygenic index repository with more phenotypes, datasets, and improved causal inference methods, enhancing predictive performance and interpretability.

This study uses Mendelian randomization to investigate the causal relationship between socioeconomic status and brain structure, finding that SES is protective against white matter hyperintensities independent of cognitive ability.

The paper finds stronger polygenic associations with educational attainment in East Germans after reunification compared to West Germans.

This study identifies genetic variants associated with income and shows they correlate with health outcomes and educational attainment.

The paper describes the Gene-SOEP dataset, a longitudinal genetic study of 2,598 individuals in Germany, providing polygenic indices for research on genetic-environment interactions.

This paper evaluates how down-sampling affects GWAS summary statistics and recommends reporting specific analyses to support their use.

This study performs a multivariate GWAS on psychiatric disorders and symptoms to identify two genetic liabilities distinguishing common mood disturbances from serious mental illnesses.

The paper examines how socioeconomic status (SES) influences brain anatomy, identifying both genetic and environmental contributions to grey matter volume across different brain regions.

The paper uses multivariate analysis to estimate heritability and genetic correlations between brain morphology and behavioral traits, identifying four genetically distinct brain clusters.

The paper constructs polygenic indexes for 47 phenotypes across 11 datasets and provides a tool to correct errors-in-variables bias when using PGIs as proxies for the additive SNP factor.

In 159,701 siblings from 17 cohorts, population GWAS overstate direct effects on height, education, smoking, cognition, depressive symptoms and age at first birth; clinical traits mostly agree across models.

The paper links genetic risk for risky behavior to reduced grey matter volume in specific brain regions using neuroimaging and polygenic risk scores.

The paper uses multivariate genomic analysis of 1.5 million people to identify genetic loci related to addiction, antisocial behavior, and health, finding over 500 loci enriched for brain-expressed genes.

This study identifies genetic loci associated with macronutrient intake and links them to health outcomes using GWAS in over 235,000 individuals.

This study finds that moderate alcohol consumption, defined as one to two daily units, is associated with reduced gray matter volume and altered white matter microstructure in middle-aged and older adults.

GWAS in over one million individuals identify 611 loci across risk tolerance and risky behaviors, revealing shared genetic architecture and implicating glutamatergic and GABAergic neurotransmission.

This study uses genome-wide association data for educational attainment and schizophrenia to identify genetic heterogeneity and novel candidate genes for schizophrenia.

This paper introduces GIV regression to estimate causal effects in non-experimental data while addressing pleiotropy and endogeneity bias, showing it provides accurate heritability estimates and reduces bias in educational attainment outcomes.

Structural equation modeling over GWAS summary statistics fits several traits jointly; across five psychiatric traits it surfaced 27 SNPs the univariate GWASs missed and sharpened polygenic scores.

This study investigates the association between CpG methylation and educational attainment, finding limited significant associations that may be influenced by confounding factors.

The paper identifies genetic variants associated with subjective well-being, depressive symptoms, and neuroticism using genome-wide association studies and proxy-phenotype analyses.